Mobile device loss prevention

ABSTRACT

A method for a mobile device to prevent loss including monitoring environmental parameters by a mobile device; storing the environmental parameters in the mobile device to form a history of the environmental parameters; applying statistical analysis to a current set of environmental parameters as compared to the history of the environmental parameters to determine a probability that the mobile device is lost; and responsive to determining the probability that the mobile device is lost exceeds a threshold, performing an action to prevent loss of the mobile device.

This application is a continuation of application Ser. No. 14/136,369filed Dec. 20, 2013 entitled “MOBILE DEVICE LOSS PREVENTION”, thedisclosure of which is incorporated in its entirety herein by reference.

BACKGROUND

1. Technical Field

The present invention relates generally to a mobile device preventingloss, and in particular, to a computer implemented method for the mobiledevice to predict the mobile device is lost based on environmentalparameters and then taking actions to alert the user.

2. Description of Related Art

Mobile devices are becoming more capable of performing complex tasks forusers across the world. Today many people rely on mobile devices for avariety of purposes including communications, mobile processingcapabilities, information retention and retrieval, gaming, etc. As thecapabilities of these mobile devices increase and miniaturizationimproves, such mobile devices are becoming more integrated into ourpersonal and work lives.

Mobile devices are by their very nature easy to be forgotten, misplaced,stolen, or otherwise lost. Such a loss includes the monetary value ofthe mobile device, the inconvenience of the loss, any improper monetarycharges which may be incurred by an unauthorized person on the lostdevice, as well as a potential loss of security for any data containedin or accessible by the mobile device. As a result, people have becomemore careful to avoid losing their mobile devices.

SUMMARY

The illustrative embodiments provide a method for a mobile device toprevent loss including monitoring environmental parameters by a mobiledevice; storing the environmental parameters in the mobile device toform a history of the environmental parameters; applying statisticalanalysis to a current set of environmental parameters as compared to thehistory of the environmental parameters to determine a probability thatthe mobile device is lost; and responsive to determining the probabilitythat the mobile device is lost exceeds a threshold, performing an actionto prevent loss of the mobile device.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The novel features believed characteristic of the invention are setforth in the appended claims. The invention itself, further objectivesand advantages thereof, as well as a preferred mode of use, will best beunderstood by reference to the following detailed description ofillustrative embodiments when read in conjunction with the accompanyingdrawings, wherein:

FIG. 1 is a block diagram of an illustrative data processing system inwhich various embodiments of the present disclosure may be implemented;

FIG. 2 is a block diagram of an illustrative network of data processingsystems in which various embodiments of the present disclosure may beimplemented;

FIG. 3 is a block diagram of a mobile device loss prevention system inwhich various embodiments may be implemented;

FIG. 4 is a flow diagram of the mobile device loss prevention system inaccordance with a first embodiment;

FIG. 5 is a flow diagram of the mobile device loss prevention system inaccordance with a second embodiment; and

FIG. 6A through 6C are block diagrams of types of database records inwhich various embodiments may be implemented.

DETAILED DESCRIPTION

Processes and devices may be implemented and utilized for preventingloss of a mobile device. In these implementations, a mobile device lossprevention system within the mobile device predicts whether the mobiledevice is lost and then takes certain actions in response to the lostprediction. These actions should alert the user or an authorized personof the lost prediction. The user or authorized person can then takesteps to recover the lost mobile device, thereby preventing loss of themobile device. These processes and apparatuses may be implemented andutilized as will be explained with reference to the various embodimentsbelow.

FIG. 1 is a block diagram of an illustrative data processing system inwhich various embodiments of the present disclosure may be implemented.Data processing system 100 is one example of a suitable data processingsystem and is not intended to suggest any limitation as to the scope ofuse or functionality of the embodiments described herein. Regardless,data processing system 100 is capable of being implemented and/orperforming any of the functionality set forth herein such as preventingloss of a mobile device.

In data processing system 100 there is a computer system/server 112,which is operational with numerous other general purpose or specialpurpose computing system environments, peripherals, or configurations.Examples of well-known computing systems, environments, and/orconfigurations that may be suitable for use with computer system/server112 include, but are not limited to, personal computer systems, servercomputer systems, thin clients, thick clients, hand-held or laptopdevices, multiprocessor systems, microprocessor-based systems, set topboxes, programmable consumer electronics, network PCs, minicomputersystems, mainframe computer systems, and distributed cloud computingenvironments that include any of the above systems or devices, and thelike.

Computer system/server 112 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 112 may be practiced in distributedcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules may be located inboth local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 112 in data processing system100 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 112 may include, but are notlimited to, one or more processors or processing units 116, a systemmemory 128, and a bus 118 that couples various system componentsincluding system memory 128 to processor 116.

Bus 118 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 112 typically includes a variety ofnon-transitory computer system usable media. Such media may be anyavailable media that is accessible by computer system/server 112, and itincludes both volatile and non-volatile media, removable andnon-removable media.

System memory 128 can include non-transitory computer system usablemedia in the form of volatile memory, such as random access memory (RAM)130 and/or cache memory 132. Computer system/server 112 may furtherinclude other non-transitory removable/non-removable,volatile/non-volatile computer system storage media. By way of example,storage system 134 can be provided for reading from and writing to anon-removable, non-volatile magnetic media (not shown and typicallycalled a “hard drive”). Although not shown, a USB interface for readingfrom and writing to a removable, non-volatile magnetic chip (e.g., a“flash drive”), and an optical disk drive for reading from or writing toa removable, non-volatile optical disk such as a CD-ROM, DVD-ROM orother optical media can be provided. In such instances, each can beconnected to bus 118 by one or more data media interfaces. Memory 128may include at least one program product having a set (e.g., at leastone) of program modules that are configured to carry out the functionsof the embodiments. Memory 128 may also include data that will beprocessed by a program product.

Program/utility 140, having a set (at least one) of program modules 142,may be stored in memory 128 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 142 generally carry out the functionsand/or methodologies of the embodiments. For example, a program modulemay be software for preventing loss of a mobile device.

Computer system/server 112 may also communicate with one or moreexternal devices 114 such as a keyboard, a pointing device, a display124, etc.; one or more devices that enable a user to interact withcomputer system/server 112; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 112 to communicate withone or more other computing devices. Such communication can occur viaI/O interfaces 122 through wired connections or wireless connections.Still yet, computer system/server 112 can communicate with one or morenetworks such as a local area network (LAN), a general wide area network(WAN), and/or a public network (e.g., the Internet) via network adapter120. As depicted, network adapter 120 communicates with the othercomponents of computer system/server 112 via bus 118. It should beunderstood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with computer system/server 112.Examples, include, but are not limited to: microcode, device drivers,tape drives, RAID systems, redundant processing units, data archivalstorage systems, external disk drive arrays, etc.

FIG. 2 is a block diagram of an illustrative network of data processingsystems in which various embodiments of the present disclosure may beimplemented. Data processing environment 200 is a network of dataprocessing systems such as described above with reference to FIG. 1.Software applications such as for preventing loss of a mobile device mayexecute on any computer or other type of data processing system in dataprocessing environment 200. Data processing environment 200 includesnetwork 210. Network 210 is the medium used to provide simplex, halfduplex and/or full duplex communications links between various devicesand computers connected together within data processing environment 200.Network 210 may include connections such as wire, wireless communicationlinks, or fiber optic cables.

Server 220, client 240 and laptop 250 are coupled to network 210 alongwith storage unit 230. In addition, mobile device 260 and facility 280(such as a home or business) are coupled to network 210 includingwirelessly such as through a network router 253. Mobile device 260 mayalso be coupled to network 210 through a mobile phone tower 262. Dataprocessing systems, such as server 220, client 240, laptop 250, mobiledevice 260 and facility 280 contain data and have software applicationsincluding software tools executing thereon. Other types of mobiledevices such as personal digital assistants (PDAs), smartphones,tablets, netbooks, laptops, etc. may be connected to network 210.

Mobile device 260 may also be wirelessly couple to tag 270 such asthrough near field communications or other short range communications.Tag 270 may be passive or active. Tag 270 allows mobile device 260 todetermine whether the tag is on the proximity of mobile device 260,among other functions. Tag 270 may include data 276 which includes anidentifier for distinguishing between multiple tags. Tag 270 may be anRFID (radio frequency identifier) or NFC (near field communications)tag.

Server 220 may include software application 224 and data 226 forpreventing loss of a mobile device or other software applications anddata in accordance with embodiments described herein. Storage 230 maycontain software application 234 and a content source such as data 236for preventing loss of a mobile device. Other software and content maybe stored on storage 230 for sharing among various computer or otherdata processing devices. Client 240 may include software application 244and data 246. Laptop 250 and mobile device 260 may also include softwareapplications 254 and 264 and data 256 and 266. Facility 280 may includesoftware applications 284 and data 286. Other types of data processingsystems coupled to network 210 may also include software applications.Software applications could include a web browser, email, or othersoftware application for preventing loss of a mobile device.

Server 220, storage unit 230, client 240, laptop 250, mobile device 260,and facility 280 and other data processing devices may couple to network210 using wired connections, wireless communication protocols, or othersuitable data connectivity. Client 240 may be, for example, a personalcomputer or a network computer.

In the depicted example, server 220 may provide data, such as bootfiles, operating system images, and applications to client 240 andlaptop 250. Server 220 may be a single computer system or a set ofmultiple computer systems working together to provide services in aclient server environment. Client 240 and laptop 250 may be clients toserver 220 in this example. Client 240, laptop 250, mobile device 260and facility 280 or some combination thereof, may include their owndata, boot files, operating system images, and applications. Dataprocessing environment 200 may include additional servers, clients, andother devices that are not shown.

In the depicted example, data processing environment 200 may be theInternet. Network 210 may represent a collection of networks andgateways that use the Transmission Control Protocol/Internet Protocol(TCP/IP) and other protocols to communicate with one another. At theheart of the Internet is a backbone of data communication links betweenmajor nodes or host computers, including thousands of commercial,governmental, educational, and other computer systems that route dataand messages. Of course, data processing environment 200 also may beimplemented as a number of different types of networks, such as forexample, an intranet, a local area network (LAN), or a wide area network(WAN). FIG. 2 is intended as an example, and not as an architecturallimitation for the different illustrative embodiments.

Among other uses, data processing environment 200 may be used forimplementing a client server environment in which the embodiments may beimplemented. A client server environment enables software applicationsand data to be distributed across a network such that an applicationfunctions by using the interactivity between a client data processingsystem and a server data processing system. Data processing environment200 may also employ a service oriented architecture where interoperablesoftware components distributed across a network may be packagedtogether as coherent business applications.

FIG. 3 is a block diagram of a mobile device loss prevention system 300in which various embodiments may be implemented. The mobile device canbe a personal digital assistant (PDA), a smartphone, a tablet, anetbook, a laptop or other type of mobile data processing system.

Mobile device loss prevention system 300 is included in the mobiledevice to prevent loss of the mobile device. That is, the mobile deviceloss prevention system may be added to the mobile device as an add-onapplication or it may be deeply incorporated into the mobile device. Themobile device loss prevention system uses environmental parameters ofthe mobile device to predict whether the mobile device is lost and thenperforms certain actions to notify the user or authorized person of thelost prediction. The user or authorized person can then take steps torecover the lost mobile device, thereby preventing loss of the mobiledevice. This system and process helps prevent loss of the mobile deviceother than for a temporary time period.

Mobile device loss prevention system includes a control system 320,environmental elements 340, action elements 360 and databases 380.Control system 320 manages the operation of the environmental elements340, action elements 360 and stores and utilizes information indatabases 380. Environmental elements 340 include various elements ordevices for determining the environmental conditions of the mobiledevice. These environmental conditions are sensed and stored asparameters for comparison purposes. Action elements 360 include variouselements or devices for notifying the user of the mobile device that themobile device may have been lost by that user. Environmental elements340 and action elements 360 may have elements in common. Databases 380are for storing information utilized to determine whether a change inenvironmental parameters indicates that the mobile device may be lost.

Control system 320 includes a processor and software or other types ofdata processing capabilities for carrying out the processes necessary toprevent loss of the mobile device. Control system may be an applicationrunning on the mobile device processor or on a separate processor withinmobile device loss prevention system 300. Control system includes aclock 322 which can be utilized to time stamp data among otherfunctions.

Environmental elements 340 include NFC/WPAN 342, WLAN 344, GPS 346,camera 348, microphone 350, sensors 352, function monitor 354 and other356. NFC/WPAN (near field communications/wireless personal area network)342 includes the capability to communicate with other devices that areeither with or in the near proximity of the user. This can include othermobile devices the user may be carrying such as a remote earpiece, atablet, a tag, or other mobile device. For example, the user may carry apassive tag in his or her wallet for use such as described below. WLAN(wireless local area network) 344 includes the capability to communicatewith wireless routers and other devices in the local area. Suchcommunications include identifying information which can be utilized todetermine the general location of the mobile device. For example, a homewireless router is easily identified and can be used to determine thatthe mobile device is not lost. GPS (global positioning system) 346 isable to determine the location of the mobile device anywhere in theworld so long as the GPS has a sufficient signal from multiplesatellites. If the mobile device is indoors, the GPS function may notfunction properly. NFC/WPAN 342, WLAN 344 and GPS 346 are locationenvironment detection elements 347 and can all be used for determiningthe relative or absolute location of the mobile device. Other suchlocating elements may also be utilized.

Camera 348 can periodically or on demand take a picture of thesurrounding of the mobile device. This picture can be analyzed fordetermining whether familiar objects or persons are nearby. For example,facial recognition technology can be utilized to identify the user orthe user's family and friends. Microphone 350 can periodically or ondemand sample ambient sounds near the mobile device. This can includewhen a phone call is being made if the mobile device is a mobile phone.These sounds can be analyzed for determining whether familiar sounds orpersons are nearby. For example, voice recognition technology can beutilized to identify the user or the user's family and friends. Sensors352 can include a variety of other environmental conditions. Forexample, an accelerometer or other motion sensor may be utilized todetermine whether the device is being moved about. An inclinometer maybe utilized to determine the orientation or changes in orientation ofthe mobile device. The accelerometer and inclinometer can also beutilized to identify the current holder of the phone through gaitanalysis or holding patterns. A thermometer may be utilized to determinethe ambient temperature. Camera 348, microphone 350 and sensors 352 areambient environment sensing elements 353 and can be utilized todetermine the ambient conditions of the mobile device. Many other typesof sensors may be similarly utilized.

Mobile device function monitor 354 can include monitoring theutilization of the mobile device such as gesturing utilized by a persontyping a text, detecting whether the mobile device is being charged,checking calendar entries, etc. Function monitor 354 is a functionalenvironment detection element 355 and can be utilized to determine howthe mobile device is being operated by a user. Other environmentalelements 356 can include other types of locating elements, sensingelements, etc., such as a sensor detecting battery depletion of thedevice, that may be utilized to determine environmental parametersuseful for determining whether the mobile device may be lost.

Action elements 360 include elements or devices within mobile deviceloss prevention system 300 for signaling or notifying the user or otherpersons that the mobile device may be lost. Action elements may includesome of the same elements as environmental elements 340. Action elements360 include speaker 362, flash 364, SMS/MMS 366, Email 368, phone 370and other action elements 372. Speaker 362 could generate a beep, avoice command, or other audible signal if a determination is made by themobile device that it may be lost. Flash 364, such as a camera or otherlight flash, may generate a series of light flashes to alert a nearbyperson that the mobile device may be lost and to the location of themobile device. Speaker 362 and flash 364 are vicinity action elements365 for alerting persons in the vicinity of the mobile device. SMS/MMS(short message service/multimedia message service) 366 can generate atext or other message to a predesignated device to alert the user orother authorized person. Email 368 can generate an email to apredesignated email account to alert the user or other authorizedperson. Phone 370 can initiated a phone call and phone message to apredesignated phone to alert the user or other authorized person.SMS/MMS 366, email 368 and phone 370 are long range action elements 371and can alert a user or other authorized person that the mobile devicemay be lost and to the location of the mobile device. Other actionelements 372 can be utilized to alert the user or other authorizedperson that the mobile device may be lost.

Databases 380 include historical data 382, configuration parameters 384and statistical parameters 386 for storing information utilized todetermine whether a change in environmental parameters indicates thatthe mobile device may be lost. Historical data 382 includes datacollected from environmental elements 340 over an extended period oftime sufficient to establish user patterns. Deviation from thesepatterns can indicate that the mobile device is lost, which can beutilized to perform a set or series of alert actions to notify the user.Configuration parameters 384 include various parameters utilized toconfigure the mobile device loss prevention system such as a homelocation, a user voice sample, a threshold deviation from standardpatterns, the preferred actions to be taken when the mobile device mayhave been lost, etc. Statistical parameters 386 include variousparameters derived from statistical analysis of historical data such asaverages and standard deviations.

FIG. 4 is a flow diagram of the mobile device loss prevention system inaccordance with a first embodiment. In a first step 400, the mobiledevice loss prevention system samples the environmental conditions ofthe mobile device. This can include determining the relative or absolutelocation of the device, determining the ambient conditions, andmonitoring the operational functions of the mobile device. Determiningthe location can include identifying any nearby devices through NFC orWPAN, identifying any routers or other wireless devices through WLAN, ordetermining the geographic location of the device through GPS.Determining the ambient conditions can include taking a picture,listening to ambient sounds, taking the temperature, determining if themobile device is being moved, and determining the orientation of thedevice. Monitoring the operational functions of the phone can includemonitoring the user using the mobile device such as user entry onto atouch screen (e.g. text entry, menu selection) and other useractivities. Many of the aforementioned actions can be occurringcontinuously as a monitoring function, but may be sampled periodicallyor as needed. Such sampling may be different for different environmentalconditions.

In a second step 405, the raw sampled data is analyzed and parametersare generated from the analytical results, thereby generating a currentset of environmental parameters. These environmental parameters caninclude absolute or relative measures such as location, probabilityanalysis of whether the current user or holder of the phone is the owneror other authorized person, or other analytical results which can becompared with past analytical results. This current set of environmentalparameters is then time stamped and stored in historical data in step408. The raw data may also be stored with the parameters if desired,although that amount of information may be excessively large for localstorage.

In a fourth step 410, the current set of environmental parameters iscompared to the historical data. This comparison can include acomparison to averages of historical data (stored in statisticalparameters) as well as to specific environmental parameters previouslystored in historical data. Then in step 415, a determination is madewhether there is a significant difference between the current set ofenvironmental parameters and the historical data. A significantdifference is the probability of the device being lost exceeding athreshold. This determination can include statistical analysis of thedeviation from the averages as well as determining whether there havebeen any close matches to specific sets of environmental parameters inthe historical data. If there is not a significant difference, thenprocessing returns to step 400, otherwise the mobile device may be lostand processing continues to step 420.

There are many possible examples of potential significant deviations.For a first example, the mobile device lost prevention system may detectunknown voices without detecting known voices in combination with thephone being in an unfamiliar location. That is, the user may have leftthe phone on a table in a restaurant. For another example, the ambienttemperature may be quite low and the phone in an unusual location. Thismay indicate that the phone is outside and not in the pocket or hand ofthe user such as if the user dropped the phone while jogging. Each ofthese examples could create unusual conditions as reflected in theenvironmental parameters detected by the mobile device loss preventionsystem.

In step 420, a first set of actions are performed in response to thedetermination that the mobile device may be lost. This set of actionsmay be set forth in the configuration database. The mobile device mayinitially generate and audible sound such as a beep and flash the mobiledevice light flash to alert the user that the mobile device may be lost.The beeping and flashing can also alert others if someone other than therightful owner of the phone is taking the phone. This alert can beturned off by the user logging into the mobile device. This prevents anunauthorized person from turning off the alert. The alert may betemporarily suspended by pressing a specific key or button to allow theuser time to log into the mobile device. Otherwise, in case of a falsepositive, the user may be in an environment that continuing the alertcould cause discomfort of the user and others. Then in step 425, it isdetermined whether the user has logged into the mobile device within apredetermined time. If yes, then processing continues to step 450,otherwise processing continues to step 430.

In step 430, a second set of actions are performed in response to thedetermination that the mobile device may be lost. This set of actionsmay also be set forth in the configuration database. The mobile devicemay send a message to another device of the user or other authorizedperson through one or more communications including text, email or phonecall. The message can include information that the mobile device may belost and include any locational information or other information (suchas temperature) which may be useful in locating the mobile device. Asbefore, this alert can be turned off by the user logging into the mobiledevice. Then in step 435, it is determined whether the user has loggedinto the mobile device within a predetermined time. If not, thenprocessing returns to step 430 to repeat the message with any updatedlocational information, otherwise processing continues to step 450.

In step 450, the user has logged into the mobile device, cancelling anyalerts. In this step, the user is queried whether the device had beenlost. The user response is determined in step 455. If yes, then in step460 the current set of environmental parameters stored in historicaldata are marked as indicating a mobile device is lost so that thoseparameters are not used in the future to indicate a normal set ofenvironmental parameters. If no, then in step 465, the statisticalparameters are updated with the current set of environmental parametersto help avoid a similar false positive. Processing then returns to step400.

FIG. 5 is a flow diagram of the mobile device loss prevention system inaccordance with a second embodiment. In this embodiment, there isgreater granularity of statistical analysis and more use of prior dataregarding mobile device lost prediction than in the first embodiment.Statistical analysis is the practice or science of collecting andanalyzing numerical data in large quantities such as for the purpose ofinferring proportions and probabilities in a whole from those in arepresentative sample.

Due to the lack of initial historical data, the mobile device lossprevention system may initially generate many false positives and falsenegatives when predicting the mobile device is lost. This can bemitigated by the use of dummy statistical data initially, which can thenbe supplanted with actual historical data over time. This dummystatistical data can be developed based on actual data of other users orwith artificial data. The user may be queried about his or heractivities when acquiring the mobile device to tailor the dummy data tothe user.

In a first step 500, the mobile device loss prevention system samplesthe environmental conditions of the mobile device. This can includedetermining the relative or absolute location of the device, determiningthe ambient conditions, and monitoring the operational functions of themobile device. Determining the location can include identifying anynearby devices through NFC or WPAN, identifying any routers or otherwireless devices through WLAN, or determining the geographic location ofthe device through GPS. Determining the ambient conditions can includetaking a picture, listening to ambient sounds, taking the temperature,determining if the mobile device is being moved, and determining theorientation of the device. Monitoring the operational functions of thephone can include monitoring the user using the mobile device such asuser entry onto a touch screen (e.g. text entry, menu selection) andother user activities. Many of the aforementioned actions can beoccurring continuously as a monitoring function, but may be sampledperiodically or as needed. Such sampling may be different for differentenvironmental conditions.

In a second step 505, the raw sampled data is analyzed and parametersare generated from the analytical results, thereby generating a currentset of environmental parameters. These environmental parameters caninclude absolute or relative measures such as location, probabilityanalysis of whether the current user or holder of the phone is the owneror other authorized person, or other analytical results which can becompared with past analytical results. This current set of environmentalparameters is then time stamped and stored in historical data in step508. The raw data may also be stored with the parameters if desired,although that amount of information may be excessively large for localstorage.

In a fourth step 510, the current set of environmental parameters iscompared to statistical parameters derived from historical data for eachtype of environmental parameter detected to determine deviations fromthe norm. The statistical parameters can include averages with standarddeviations, probabilities based on prior historical data, and otherstatistical measures which can be compared with the currentenvironmental parameters. A probability that the mobile device is lostis based on these individual environmental parameter deviations is thengenerated in step 513.

Then in step 515, the current set of environmental parameters iscompared to detected correlations developed from historical data todetermine deviations from the norm. For example, historical data maydemonstrate a significant correlation between ambient temperature andmotion. That is, whenever the mobile device is outside in cooler orwarmer temperatures, the user is moving such as by exercising. Thesecorrelations may also be time sensitive. That is, the correlationdescribed above may occur in the morning, but not the evening. Aprobability that the mobile device is lost is based on environmentalparameter deviations from these correlations is then generated in step518.

In step 520, the current set of environmental parameters is compared toprior historical samples stored in historical data to determine how manytimes which there have been similar environmental parameters. From thisinformation, such as a percentage of samples that are similar (or not),a statistical probability that the mobile device is lost can bedetermined based on this similarity sample information in step 523.

In step 525, the current step of environmental parameters is compared toprior historical incidents stored in historical data where the mobiledevice was lost, as confirmed by the user, to determine how many timeswhich there have been similar environmental parameters. This informationcan then be used to determine a statistical probability that the mobiledevice is lost is based on similarity with prior lost environmentalparameters in step 528.

Then in step 530, the above described probabilities that the mobiledevice is lost are weighted and combined to generate an overallprobability that the mobile device is lost. Other forms of combiningprobabilities can be utilized including weighting the probabilitiesbased on statistical confidence in each individual probability. Then instep 533, the lost probability is reduced if certain parameterconditions are identified. For example, if the device is plugged in anda known voice is heard, then the probability may be reduced based onprior knowledge or other information beyond the historical samples. Foranother example, if the calendaring function of the mobile deviceindicates a change in location, then more movement than normal may beexpected.

Once the final probability that the mobile device is lost has beendetermined, then in step 535 an overall determination is made whetherthere is a significant difference between the current set ofenvironmental parameters and the historical data (including statisticaldata derived from that historical data). A significant difference isindicated by the probability of the device being lost exceeding athreshold. The threshold can include statistical confidence levels suchthat certain confidence levels of a given lost probability are needed toexceed the threshold. If there is not a significant difference, thenprocessing returns to step 500, otherwise the mobile device may be lostand processing continues to step 540.

There are many possible examples of potential significant deviations.For a first example, the mobile device lost prevention system may detectunknown voices without detecting known voices in combination with thephone being in an unfamiliar location. That is, the user may have leftthe phone on a table in a restaurant. For another example, the ambienttemperature may be quite low and the phone in an unusual location. Thismay indicate that the phone is outside and not in the pocket or hand ofthe user such as if the user dropped the phone while jogging. Each ofthese examples could create unusual conditions as reflected in theenvironmental parameters detected by the mobile device loss preventionsystem.

In step 540, a first set of actions are performed in response to thedetermination that the mobile device may be lost. This set of actionsmay be set forth in the configuration database. The mobile device mayinitially generate and audible sound such as a beep and flash the mobiledevice light flash to alert the user that the mobile device may be lost.The beeping and flashing can also alert others if someone other than therightful owner of the phone is taking the phone. This alert can beturned off by the user logging into the mobile device. This prevents anunauthorized person from turning off the alert. The alert may betemporarily suspended by pressing a specific key or button to allow theuser time to log into the mobile device. Otherwise, in case of a falsepositive, the user may be in an environment that continuing the alertcould cause discomfort of the user and others. Then in step 543, it isdetermined whether the user has logged into the mobile device within apredetermined time. If yes, then processing continues to step 550,otherwise processing continues to step 545.

In step 545, a second set of actions are performed in response to thedetermination that the mobile device may be lost. This set of actionsmay also be set forth in the configuration database. The mobile devicemay send a message to another device of the user or other authorizedperson through one or more communications including text, email or phonecall. The message can include information that the mobile device may belost and include any locational information or other information (suchas temperature, pictures of the surroundings, name of closest WLAN,etc.) which may be useful in locating the mobile device. The GPS unitmay be turned on to determine the geographic location of the mobiledevice. Other actions can be taken to maximize the probability ofnotifying the owner or other authorized person of the location of themobile device including sending logs of the handler's activities withthe phone. As before, this alert can be turned off by the user logginginto the mobile device. Then in step 548, it is determined whether theuser has logged into the mobile device within a predetermined time. Ifnot, then processing returns to step 545 to repeat the message with anyupdated locational information, otherwise processing continues to step550. The first and second set of actions may be configurable by theuser. For example, the first set of actions may not be performed or maybe performed more vigorously depending on the configuration or thecircumstances. For another example, if it is apparent that the mobiledevice has just been absconded, then the beeping and flashing may be atmaximum intensity and for a long duration without allowing the handlerto suspend the alert. Furthermore, the second set of actions may beperformed concurrently with the first set of actions.

In step 550, the user has logged into the mobile device, cancelling anyalerts. In this step, the user is queried whether the device had beenlost. The user response is determined in step 552. If yes, then in step554 the current set of environmental parameters stored in historicaldata are marked as indicating a mobile device is lost so that thoseparameters are not used in the future to indicate a normal set ofenvironmental parameters. If no, then in step 556, the statisticalparameters are updated with the current set of environmental parametersto help avoid a similar false positive. Processing then returns to step500.

Many other configurations may be implemented in alternative embodiments.For example, the historical data may be periodically uploaded to acentral server for performing detailed statistical analysis fordetermining the statistical parameters and perhaps modifying theconfiguration parameters. This provides for a more distributed system ofprocessing environmental parameters.

FIG. 6A through 6C are block diagrams of types of database records inwhich various embodiments may be implemented. A record is a set ofinformation within a domain or database that establishes a relationshipbetween a set of data or data elements. A record may be a separate entryinto a database, a set of links between data, or other logicalrelationship between a set of data.

FIG. 6A is a block diagram of a record 600 stored in a historical datadatabase. There is a single record for each recorded set ofenvironmental parameters for a mobile device environmental conditionsample, although alternative embodiments may differ. Raw data is notstored in this database, although alternative embodiments may do so. Allparameters stored in this database are considered environmentalparameters, although they are categorized by type as describe herein.Each set of parameters described below may contain more than oneparameter.

Each record 600 includes a timestamp 601, location parameters 602,ambient parameters 603, operational functionality parameters 604,derivative parameters 605, other parameters 606, and a lost flag 607indicating whether the sampled environment was an actual mobile devicelost as confirmed by the user. Timestamp 601 is the time the particularsample was taken to generate the parameters. Location parameters 602include a set of parameters regarding the relative or absolute locationof the mobile device. Ambient parameters 603 include a set of parametersdescribing the ambient conditions of the mobile device such astemperature and motion. Operational functionality parameters 604 includea set of parameters regarding the functionality of the mobile devicesuch as typing speed or angle of finger placement of the user on themobile device. Derivative parameters 605 include a set of parameterswhich may be derived from the foregoing sets of parameters. For example,based on several parameters, a predictive value can be made of whetherthe holder of the mobile device is the user. Other parameters 606include a set of environmental parameters other than described above.Lost flag 607 is a flag generated when the user confirms that thisparticular sample corresponds to conditions when the mobile device waslost.

FIG. 6B is a block diagram of a record 620 stored in a configurationparameters database. Record 620 includes a variety of informationutilized to configure the operation of the mobile device loss preventionsystem. Each of the below described elements may include multiple setsof information utilized to configure the loss prevention system. Record620 includes user information 621, authorized person information 622,location information 623, other device information 624, lost probabilityweighting 625, probability reduction parameters 626, thresholdprobability 627, first actions 628 and second actions 629.

User information 621 provides a variety of information regarding theuser including name, contact information, facial recognition parameters,voice recognition parameters, gesturing parameters, etc. Thisinformation can be utilized to recognize the user as well as contact theuser if the mobile device is possibly lost. Authorized personinformation 622 includes similar information to user information 621 forsimilar purposes. For example, a spouse of the user may be an authorizedperson. Location information 623 includes information regarding knownlocations such as the user's home, place of work, WLAN devices at thoselocations, frequented other location information, etc. This informationmay be utilized to determine whether the mobile device is in a knownlocation or an unknown location. This information may also be utilizedto provide information the user or authorized person of the location ofthe mobile device. Other device information 624 includes informationregarding other devices normally utilized by the user including anearpiece, a tag, a tablet or mobile phone, etc.

Lost probability weighting 625 includes the weighting utilized todetermine an overall probability of use or the algorithm utilized todetermine a weighting. Probability reduction parameters 626 includecertain non-historical parameters or combinations of parameters thatindicate that the device is not lost or indicate that it is lost.Threshold probability 627 includes a threshold utilized to determinewhether the determined probability that the mobile device is lost issufficient to take action to contact and notify the user or authorizedperson of the lost prediction. First actions 628 includes the actionstaken when it is determined that the mobile device is lost. Secondactions 629 includes the actions taken when it is determined that themobile device is lost. Alternative embodiments may utilize differentconfiguration parameters. In addition, many other types of configurationparameters may be utilized and stored in this database.

FIG. 6C is a block diagram of records 640 and 660 stored in astatistical parameters database. Records 640 and 660 include informationuseful for performing statistical analysis to determine whether themobile device is lost. This statistical information is generally derivedfrom the historical data. There are two types of records shown in thestatistical parameters database. The first record 640 is used forstoring information regarding different sampled environmental parametersused for statistical analysis. For example, there may be a record forall samples of temperature and another record for all samples oflocation. Record 640 includes sample parameter description 641, sampleparameter distribution type 642, sample parameter average 643, sampleparameter standard deviation 644 and sample parameter number 645. Thesecond record 660 is used for storing information regarding differentcorrelations used for statistical analysis. Record 660 includescorrelation type 661, correlation distribution 662, correlation average663, correlation standard deviation 664, and correlation number 665.

Sample parameter description 641 includes a description of the parametersample. For example, it could include the term temperature if samples ofthe temperature are statistically described in this record. Sampleparameter distribution type 642 includes the type of distribution of theparameter sampled. For example, the result of the sampling may generatea normal curve, a uniform distribution, a bimodal normal distribution, aPoisson distribution, etc. The remaining elements of the record may varydepending on the distribution, but are described as if the sampledistribution is a normal distribution. Sample parameter average 643includes the average of all the samples of the parameter. Sampleparameter standard deviation 644 includes the standard deviation of allthe samples of the parameter. Sample parameter number 645 includes thenumber of samples used to generate the average and standard deviation.This number is important in providing a confidence level in anypredicted lost probability.

Correlation type 661 includes a description of the type correlationprovided. For example, the correlation may be between temperature andlocation. Correlation distribution 662 includes the type of distributionof the parameter sampled. For example, the result of the sampling maygenerate a normal curve, a uniform distribution, a bimodal normaldistribution, a Poisson distribution, etc. The remaining elements of therecord may vary depending on the distribution, but are described as ifthe sample distribution is a normal distribution. Correlation average663 includes the average of all the samples of the correlation.Correlation standard deviation 664 includes the standard deviation ofall the samples of the correlation. Correlation number 665 includes thenumber of samples used to generate the average and standard deviation.This number is important in providing a confidence level in anypredicted lost probability.

The type of information stored in each of the above described databasescan vary significantly depending on the type of environmental parameterssampled, the configuration of the loss prevention system, and thestatistical analysis performed. Many other types of information can begathered and utilized for predicting whether the mobile device may belost.

The invention can take the form of an entirely software embodiment, oran embodiment containing both hardware and software elements. In apreferred embodiment, the embodiments are implemented in software orprogram code, which includes but is not limited to firmware, residentsoftware, and microcode.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, microcode, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer usablemedium(s) having computer usable program code embodied thereon.

Any combination of one or more computer usable medium(s) may beutilized. The computer usable medium may be a computer usable signalmedium or a non-transitory computer usable storage medium. A computerusable storage medium may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer usable storage medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM), or Flashmemory, an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer usable storage medium may be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

A computer usable signal medium may include a propagated data signalwith computer usable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electromagnetic, optical, or any suitable combination thereof. Acomputer usable signal medium may be a computer usable medium that isnot a computer usable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer usable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing. Further, a computer storage medium may contain or store acomputer-usable program code such that when the computer-usable programcode is executed on a computer, the execution of this computer-usableprogram code causes the computer to transmit another computer-usableprogram code over a communications link. This communications link mayuse a medium that is, for example without limitation, physical orwireless.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage media, and cache memories, which provide temporary storage of atleast some program code in order to reduce the number of times code mustbe retrieved from bulk storage media during execution.

A data processing system may act as a server data processing system or aclient data processing system. Server and client data processing systemsmay include data storage media that are computer usable, such as beingcomputer readable. A data storage medium associated with a server dataprocessing system may contain computer usable code such as forpreventing loss of a mobile device. A client data processing system maydownload that computer usable code, such as for storing on a datastorage medium associated with the client data processing system, or forusing in the client data processing system. The server data processingsystem may similarly upload computer usable code from the client dataprocessing system such as a content source. The computer usable coderesulting from a computer usable program product embodiment of theillustrative embodiments may be uploaded or downloaded using server andclient data processing systems in this manner.

Input/output or I/O devices (including but not limited to keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modem and Ethernet cards are just a few of thecurrently available types of network adapters.

The description of the present invention has been presented for purposesof illustration and description, and is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the art. Theembodiment was chosen and described in order to explain the principlesof the invention, the practical application, and to enable others ofordinary skill in the art to understand the invention for variousembodiments with various modifications as are suited to the particularuse contemplated.

The terminology used herein is for the purpose of describing particularembodiments and is not intended to be limiting of the invention. As usedherein, the singular forms “a”, “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method for a mobile device to prevent losscomprising: monitoring environmental parameters by the mobile deviceincluding location and ambient conditions to determine a generallocation of the mobile device and to determine whether any person inproximity of the mobile device is authorized: storing the environmentalparameters, including location and ambient conditions to determine thegeneral location of the mobile device and to determine whether anyperson in proximity of the mobile device is authorized, to form ahistory of the environmental parameters; applying statistical analysisto a current set of environmental parameters monitored by the mobiledevice, including the location and ambient conditions to determine thegeneral location of the mobile device and to determine whether anyperson in proximity of the mobile device is authorized based on theenvironmental parameters, as compared to the history of theenvironmental parameters to determine a probability that the mobiledevice is lost; wherein the statistical analysis applied to the currentset of environmental parameters includes correlations between aplurality of environmental parameters including a correlation betweenthe general location of the mobile device and whether an authorizedperson is in proximity of the mobile device to determine a probabilitythat the mobile device is lost; and responsive to determining theprobability that the mobile device is lost exceeds a threshold,performing an action to prevent loss of the mobile device.
 2. The methodof claim 1 wherein the environmental parameters monitored and applied tostatistical analysis include operational functions performed by the useroperating the mobile device to determine whether the user is anauthorized person.
 3. The method of claim 2 wherein the environmentalparameters are selected from a group consisting of geographic location,temperature, device motion, device orientation, image capture analysis,audio capture analysis, battery depletion of the device, and analysis ofthe operational functionality of the device.
 4. The method of claim 3further comprising: generating statistical derivatives of the history ofenvironmental parameters; wherein applying statistical analysis to acurrent set of environmental parameters as compared to the history ofthe environmental parameters includes applying statistical analysis tostatistical derivatives of the history of the environmental parameters;wherein the statistical analysis applied to the environmental parametersincludes correlations between a plurality of environmental parametersincluding the general location of the mobile device and the ambientconditions to determine a probability that the mobile device is lost;wherein the action is selected from a group consisting of an audiblealert, flashing a light, texting information to another device, emailinginformation to another device, and phoning information to anotherdevice; and wherein the mobile device is selected from a groupconsisting of a personal digital assistant (PDA), a smartphone, atablet, a netbook and a laptop.
 5. The method of claim 2 furthercomprising: generating statistical derivatives of the history ofenvironmental parameters; wherein applying statistical analysis to acurrent set of environmental parameters as compared to the history ofthe environmental parameters includes applying statistical analysis tostatistical derivatives of the history of the environmental parameters.6. The method of claim 2 wherein the correlations between the pluralityof environmental parameters includes detecting unknown voices withoutdetecting known authorized voices in combination with the mobile beingin an unfamiliar location to determine a probability that the mobiledevice is lost.
 7. The method of claim 6 wherein the correlationsbetween the plurality of environmental parameters includes operationalfunctions performed on the device.
 8. The method of claim 1 wherein theaction is selected from a group consisting of an audible alert, flashinga light, texting information to another device, emailing information toanother device, and phoning information to another device.
 9. The methodof claim 1 wherein the mobile device is selected from a group consistingof a personal digital assistant (PDA), a smartphone, a tablet, a netbookand a laptop.
 10. The method of claim 1 wherein the ambient conditionsare selected from a group consisting of sound, camera input andtemperature.
 11. The method of claim 10 wherein the location and ambientconditions are sensed by mobile device sensors selected from the groupof microphone, camera, thermometer, accelerometer, and inclinometer. 12.The method of claim 1 further comprising determining whether a passivetag carried by the authorized person is no longer within proximity ofthe mobile device wherein the passive tag determination is utilized todetermine whether the authorized person is in proximity of the mobiledevice.
 13. A method for a mobile device to prevent loss comprising:monitoring environmental parameters by the mobile device including ageneral location of the mobile device, whether any person in proximityof the mobile device is authorized, and operational functions performedby the user operating the mobile device to determine whether the user isthe authorized person; storing the environmental parameters includingthe general location of the mobile device, whether any person inproximity of the mobile device is authorized, and operational functionsperformed by the user operating the mobile device to form a history ofthe environmental parameters; applying statistical analysis to a currentset of environmental parameters including the general location, whetherany person in the proximity of the mobile device is authorized based onthe environmental parameters, and operational functions monitored by themobile device including a correlation between the general location ofthe mobile device, whether any person in proximity of the mobile deviceis authorized and operational functions performed by the user operatingthe mobile device as compared to the history of the environmentalparameters to determine a probability that the mobile device is lost;and responsive to determining the probability that the mobile device islost exceeds a threshold, performing an action to prevent loss of themobile device.